Multi-component picture or video coding concept

ABSTRACT

The coding efficiency of a multi-component picture or video coding concept is improved by reconstructing a third component signal relating to a third component of the multi-component video using inter-component prediction from both a reconstructed first component signal and a reconstructed second component signal.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of copending InternationalApplication No. PCT/EP2014/072350, filed Oct. 17, 2014, which isincorporated herein by reference in its entirety, and additionallyclaims priority from European Application No. EP 13 189 444.6, filedOct. 18, 2013, which is also incorporated herein by reference in itsentirety.

BACKGROUND OF THE INVENTION

The present invention is concerned with multi-component picture or videocoding such as the coding of color pictures or videos.

Colored images and videos are represented using a so-called color spacewith either three or four dimensions and the dimensions are alsoreferred to as components. An example for a three-component color spaceis the R′G′B′ color space. In this color space, the primaries red (R′),green (G′), and blue (B′) form the basis of the three dimensional colorcube. In the signal processing application space, however, it is crucialto minimize the correlation between the different components in order toachieve high efficiency in terms of power consumption, implementationcosts, or compression efficiency in the case of image and videocompression. Therefore, R′G′B′ signals are often converted toY′C_(b)C_(r) with the first component (Y′) being referred to as the lumaand the remaining two components (C_(b)C_(r)) being referred to as thechroma components. In contrast to the R′G′B′ color space, the chromacomponent values of Y′C_(b)C_(r) represent a color difference relativeto the blue or the red primary. Consequently, the chroma energy is oftenreduced and hence leads to higher compression efficiency. However, dueto the application of a fixed transform, i.e., the R′G′B′ toY′C_(b)C_(r) conversion, the resulting output is often not locallyoptimal. A possibility to overcome such kind of limitations is theapplication of a local prediction between the color components. Such aprediction is often referred to as inter-component prediction (ICP). TheICP can be applied to both R′G′B′ and Y′C_(b)C_(r) signals. In the firstcase, the ICP would result in an energy reduction for the chromacomponents, and hence, it can be treated as a replacement for theexternal color space conversion. In the second case, the ICP approachcan be treated as a further decorrelation step between the differentcolor components, and hence, the ICP approach results in highercompression efficiency. For the sake of simplification, regardless ofthe native or input color space, the remaining description refers toluma or Y′ to denote the first and the main component and first orsecond chroma, or respectively C_(b) or C_(r), to denote the tworemaining chroma components. It is important to note that the order ofthe chroma components can be important as the processing order can besequential for some applications.

ICP is, if ever, applied pair-wise, such as for example by predictingone chroma component on the basis of the luma component and doing thesame for the other chroma component. It would be favorable, however, tobe able to further increase the coding efficiency.

SUMMARY

An embodiment may have a decoder configured to decode a multi-componentpicture or video spatially sampling a scene with respect to differentcomponents, by reconstructing a first component signal relating to afirst component of the multi-component picture or video from a datastream; reconstructing a second component signal relating to a secondcomponent of the multi-component picture or video from the data stream;reconstructing a third component signal relating to a third component ofthe multi-component picture or video using inter-component predictionfrom the reconstructed first component signal and the reconstructedsecond component signal.

According to another embodiment, a method for decoding a multi-componentpicture or video spatially sampling a scene with respect to differentcomponents may have the steps of: reconstructing a first componentsignal relating to a first component of the multi-component picture orvideo from a data stream; reconstructing a second component signalrelating to a second component of the multi-component picture or videofrom the data stream; reconstructing a third component signal relatingto a third component of the multi-component picture or video usinginter-component prediction from the reconstructed first component signaland the reconstructed second component signal.

Another embodiment may have an encoder configured to encode amulti-component picture or video spatially sampling a scene with respectto different components, by encoding a first component signal relatingto a first component of the multi-component picture or video into a datastream; encoding a second component signal relating to a secondcomponent of the multi-component picture or video into the data stream;encoding a third component signal relating to a third component of themulti-component picture or video using inter-component prediction fromthe encoded first component signal and the encoded second componentsignal.

According to another embodiment, a method for encoding a multi-componentpicture or video spatially sampling a scene with respect to differentcomponents may have the steps of: encoding a first component signalrelating to a first component of the multi-component picture or videointo a data stream; encoding a second component signal relating to asecond component of the multi-component picture or video into the datastream; encoding a third component signal relating to a third componentof the multi-component picture or video using inter-component predictionfrom the encoded first component signal and the encoded second componentsignal.

Another embodiment may have a non-transitory digital storage mediumhaving a computer program stored thereon to perform the inventivemethods when said computer program is run by a computer.

It is a basic finding of the present application that the codingefficiency of a multi-component picture or video coding concept may beimproved by reconstructing a third component signal relating to a thirdcomponent of the multi-component video using inter-component predictionfrom both a reconstructed first component signal and a reconstructedsecond component signal.

In accordance with an embodiment of the present application, a multiplesource ICP signalization in the data stream is used so as to switch, fordifferent or in units of ICP mode portions of the multi-componentpicture or video, between different ICP coding modes. The ICP codingmodes include a multiple source ICP coding mode and at least one non-ICPcoding mode. In ICP mode portions of the multi-component picture orvideo for which the multiple source ICP coding mode applies, forsub-portions of a picture of the multi-component picture or video, asignalization is provided in the data stream indicating for eachsub-portion whether same is inter-component predicted from the spatiallycorresponding portion of the reconstructed first component signal, thespatially corresponding portion of the reconstructed second componentsignal or a combination of both. In the at least one non-ICP codingmode, such a combination or change between the spatially correspondingportion of the reconstructed first component signal and the spatiallycorresponding portion of the reconstructed second component signal isnot available. ICP may be switched off completely in ICP mode portionsof a non-ICP coding mode, or ICP may be available merely with respect toa fixed one of the first and second component signals. The ICP modeportions may be single pictures, single picture sequences or singleslices or consecutively coded pictures, picture sequences or slices. Bythe juxtaposition of the multiple source ICP coding mode with at leastone non-ICP coding mode, any additional signalization overhead, which inaccordance with embodiments of the present application may be involvedwith the sub-picture wise parameterization of the multi-source ICP andmay by increased in the case of the multiple source ICP coding moderelative to a non-ICP coding mode, may be restricted to portions of thevideo where this additional signalization overhead is overcompensated bythe coding efficiency gains obtained by the more than one componentsource available for inter-component prediction.

In accordance with an embodiment, the first component is luma, thesecond component is a first chroma component and a third component is asecond chroma component. In that case, the combined inter-componentprediction of the second chroma component on the basis of the lumacomponent and the first chroma component further improves decorrelatingthe residuals to be coded using, for instance, transform and entropycoding.

In accordance with an embodiment, explicit ICP source signalization inthe data stream is used so as to switch, at sub-picture granularity,between reconstructing the third component signal in a current pictureof the multi-component picture or video using inter-component predictionfrom a spatially corresponding portion of the reconstructed firstcomponent signal and reconstructing the third component signal in thecurrent picture of the multi-component picture or video usinginter-component prediction from a spatially corresponding portion of thereconstructed second component signal. Despite the signalizationoverhead, the prediction improvement available by this meansovercompensates the signalization overhead, thereby yielding highercoding efficiency. Alternatively, implicit signalization may be used.Irrespective of the type of signalization used, the sub-picturegranularity may coincide with a granularity at which the reconstructionof the third component signal switches between spatial, temporal and/orinter-view prediction modes, i.e. both switching between spatial,temporal and/or inter-view prediction modes in reconstructing the thirdcomponent signal as well as the switching between performing ICP basedon the first component signal and the second component signal,respectively, may be performed in units of prediction blocks or—usingdifferent wording—coding units. Alternatively, transform blocks may beused.

The ICP may be performed using linear prediction. In doing so, ICPprediction parameter signalization in the data stream may be used so asto vary weights at which the reconstructed first component signal andthe reconstructed second component signal linearly contribute to theinter-component prediction at sub-picture granularity. That is, twoweights may be transmitted in the data stream at the sub-picturegranularity, one of which signaling the weight for the reconstructedfirst component signal and the other indicating the weight for thereconstructed second component signal so that the weighted sum of bothyields the inter-component prediction using the two sources. Using thelinear prediction, the ICP prediction parameter signalization overheadmay be kept at a reasonable cost while nevertheless achieving sufficientdecorrelation improvement. As indicated above, the weights may besignaled in the data stream in units of prediction blocks or transformblocks. The available values for the weights may be distributed aroundzero and may include zero.

In accordance with an embodiment, the just-outlined ICP predictionparameter signalization may involve a conditional signalization of anICP source indicator: a weight for a respective block is transmittedfirst, and merely in the case of same being non-zero is the ICP sourceindicator signaled. By this measure, the signaling overhead associatedwith the ICP prediction parameter signalization is additionally reduced.

In accordance with an embodiment, the ICP prediction parametersignalization comprises the coding of the weights in a manner so thatthe weights' sign is coded first with the absolute value of the weightsbeing coded subsequently using context-modeling depending on the sign.By this measure, the probability used to entropy code/decode theabsolute value may be set dependent on the sign, thereby resulting in animproved compression rate due to a closer adaptation of the probabilityused.

In accordance with an embodiment of the present application, theinter-component prediction is applied onto a prediction residual of aspatial/temporal and/or inter-view prediction used in reconstructing thethird component signal in an intra-component manner. In other words, theinter-component prediction represents a kind of second-stage predictionrelative to the spatial, temporal and/or inter-view intra-componentprediction of the third component signal. Likewise, the reconstructedfirst component signal and the reconstructed second component signal mayrepresent prediction residuals of intra-component spatial, temporaland/or inter-view predictions performed with respect to the first andsecond components of the multi-component picture or video signal.

The inter-component prediction may be performed in the spatial domain orthe spectral domain.

In accordance with another embodiment, explicit ICP source signalizationin the data stream is used to switch between the available ICP sourcesat a first sub-picture granularity, while ICP prediction parametersignalization in the data stream is used so as to adjust a predictionmodel by way of which the ICP is performed with respect to the signaledICP source, wherein the entropy coding/decoding of the explicit ICPsource signalization involves the usage of a context model which isdependent on the prediction parameter of the prediction model adjustedat a second granularity according to the ICP prediction parametersignalization. By this measure, correlation between both signalizations,i.e. ICP source signalization and ICP prediction parametersignalization, may be exploited to further reduce the signalingoverhead.

In accordance with a further embodiment, swap signalization in the datastream is used so as to swap the reconstructed third component signaland the reconstructed second component signal. For example, within onepicture the swap signalization changes the order at a sub-picturegranularity among first, second and third components so that, forexample, within one picture one sub-block has available luma and firstchroma component for inter-component predicting the second chromacomponent, while another sub-block has available luma component andsecond chroma component for inter-component predicting the first chromacomponent.

In accordance with an embodiment, the coding of an ICP source indicatorfor a certain block of a picture is rendered dependent on a differenceof a previously coded ICP prediction parameter signalization for thethird component and the ICP prediction parameter signalization for thesecond component: if the difference exceeds a predetermined limit, theICP source indicator is absent for the respective block. The ICP sourceindicator may, in that case, be inferred to denote the reconstructedsecond component signal as ICP source for the third component signal. Inother words, if the ICP prediction parameters sent for the current blockare sufficiently similar as far as the ICP with respect to the secondand third components are concerned, it may be assumed that the componentsignals of all components are quite similar with the ICP sourceindicator indicating the reference for ICP for the third component, andif the ICP prediction parameters differ, it may be assumed that the ICPfor the third component uses the second component as a basis while theICP for the second component uses the first component as a basisinstead. The first case is more likely to occur in case of RGB colorcomponents and the second more likely to occur in case of YCC colorcomponents. By this measure, coding efficiency may be increased bylowering the side information overhead for the ICP signaling.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present invention will be detailed subsequentlyreferring to the appended drawings, in which:

FIG. 1 shows a block diagram of a decoder in accordance with anembodiment of the present application;

FIG. 2 shows a block diagram of a decoder of an embodiment of thepresent application applying the ICP onto intra-component predictionresiduals;

FIG. 3 shows a block diagram of an encoder fitting to the decoder ofFIG. 1 in accordance with an embodiment;

FIG. 4 shows a block diagram of an encoder fitting to the decoder ofFIG. 2 in accordance with an embodiment;

FIG. 5a shows a schematic diagram of an embodiment according to which amultiple source ICP signalization is able to switch on and off multiplesource ICP;

FIG. 5b shows a block diagram of an embodiment for the multi-source ICPmodule according to an embodiment where ICP signalization comprises anICP prediction mode parameter in form of a weight and ICP sourceindicator;

FIG. 5c shows a block diagram of an embodiment for the multi-source ICPmodule according to an embodiment where ICP signalization comprises anICP prediction mode parameter in form of a weight per available ICPsource;

FIG. 5d,e show block diagrams of an embodiment for the multi-source ICPmodule according to FIGS. 5b and 5c , respectively, with themulti-source ICP performed in spatial domain;

FIG. 5f,g show block diagrams of an embodiment for the multi-source ICPmodule according to FIGS. 5b and 5c , respectively, with themulti-source ICP performed in spectral domain;

FIG. 6 shows a flow diagram of a treatment of ICP parameter data atdecoder and encoder in accordance with an embodiment where the ICPparameter data for the third component comprises a weight and a sourceflag;

FIG. 7 shows a flow diagram illustrating the treatment of the ICPparameter data for the third component in accordance with an embodimentaccording to which the ICP parameter data comprises weights for aweighted sum of the available ICP sources;

FIG. 8 shows a schematic diagram illustrating the treatment if ICPparameter data for the second and third components in case of usingswapping components in order to improve the ICP efficiency;

FIG. 9 shows a schematic diagram of a picture so as to illustrate thepossibility of signaling source flag and weight at differentgranularities.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 shows a decoder in accordance with an embodiment of the presentapplication. The decoder is generally indicated using reference sign 10and is configured to decode a multi-component video spatially sampling ascene with respect to different components from a data stream. Inparticular decoder 10 comprises an input at which the data stream 12enters decoder 10, and an output at which the multi-component video asreconstructed by the decoding is output, namely output 14. FIG. 1illustrates the multi-component video at 16 as comprising one picture 18per one of three components A, B and C for each time instant byexemplarily depicting pictures 18 belonging to one time instant as beingarranged one on top of the other with the temporal axis runninghorizontally. However, it should be noted that there may be more thanthree components. As outlined above and further outlined below, thecomponents A, B and C may be color components such as R, G and B or oneluma and two chroma components or the like. Alternatively, however, thecomponents may relate to another property of the scene such as, forexample, components relating to other wavelengths residing outside thevisible wavelength range or the like. Moreover, the components are notrestricted to frequencies or fragments out of an electromagneticspectrum of the scene. Rather, the components may relate, for example,at least partially to other physical parameters such as, for example,reflectivity or the like. Although FIG. 1 suggests that the pictures 18of different components are of the same size and accordingly spatiallysample the scene at the same spatial resolution, the spatial resolutionmay differ among the components. The latter circumstance could inprinciple also apply to the temporal resolution. That is, the picturerate could differ among the components A to C. If not differing, theterm “picture” may alternatively be used to denote the samples of allcomponents A to C at one time instant commonly,

Internally, decoder 10 comprises a first module 20 for reconstructing afirst component signal 22 relating to a first component A of themulti-component video 16 from the data stream 12, as well as a secondmodule 24 for reconstructing a second component signal 26 relating to asecond component B of the multi-component video 16 from the data stream12, and a module 28 for reconstructing a third component signal 30relating to a third component C of the multi-component video 16, whereinthe latter module 28 has an input connected to outputs of first andsecond modules 20 and 24 so as to use inter-component prediction fromthe reconstructed first component signal and the reconstructed secondcomponent signals 22 and 26 in reconstructing the third component signal30. As module 28 uses signals 22 and 26 of first and second components Aand B for reconstructing the third component signal relating tocomponent C, the inter-component prediction used by module 28 may beimproved, thereby increasing the coding efficiency achievable by thecodec to which decoder 10 of FIG. 1 belongs.

As will be outlined in more detail below, modules 20, 24 and 28 may infact be parts of hybrid-based decoding branches, with one suchhybrid-based decoding branch present for each component A, B and C. InFIG. 1, such decoding branches are illustrated by dashed lines 32 _(A),32 _(B) and 32 _(C), with coding branch 32 _(A) comprising module 20 andbeing configured to reconstruct the first component A from data stream12, the coding branch 32 _(B) comprising module 24 and being configuredto reconstruct component B from data stream 12 and decoding branch 32_(C) comprising module 28 and being configured to reconstruct componentC from data stream 12. In particular, as will be outlined in more detailbelow, the first and second component signals 22 and 26 reconstructed bymodules 20 and 24 and used for inter-component prediction by module 28may in fact represent prediction residuals: the reconstructed firstcomponent signal 22, for instance, may represent a prediction residualof an intra-component prediction performed by decoding branch 32 _(A),i.e. of a prediction performed by module 20 solely on the basis ofalready reconstructed portions of pictures 18 of component A—solelybased on already reconstructed component A picture samples—, wherein theintra-component prediction may be spatial, temporal and/or inter-viewprediction. Likewise, the second component signal 26 may represent aprediction residual of an intra-component prediction performed bydecoding branch 32 _(B), i.e. a prediction solely based on alreadyreconstructed portions of pictures 18 of component B, wherein thisintra-component prediction may be spatial, temporal and/or intra-viewprediction. Likewise, the reconstructed third component signal 30 mayalso represent a prediction residual of an intra-component predictionperformed by decoding branch 32 _(C), i.e. of a prediction solelyperformed on the basis of already reconstructed portions of pictures 18of component C, wherein this intra-component prediction may also bespatial, temporal and/or inter-view prediction. The intra-viewprediction performed by modules 20, 24 and/or 28 may vary in terms ofprediction mode, i.e. whether spatial, temporal and/or inter-viewprediction is used. For example, the prediction mode vary at agranularity of coding units or—using a different wording—predictionblocks, i.e. sub-portions of pictures 18, with the prediction mode to beused for a respective coding unit or prediction block being signalizedin the data stream 12. The prediction mode may be signaled in the datastream 12 for components A, B and C commonly or individually or, evenfurther, for the first component A on the one hand and the second andthird components B and C on the other hand separately. In addition tothis intra-component prediction signalization in data stream 12, modules20, 24 and 28 receive component-specific signaled prediction residualdata. The prediction residual data may be transmitted in the data streamin a transform domain, in the form of transform coefficients of aspectral decompositions, or in spatial domain, i.e. in the form ofresidual samples. If signaled in the spectral domain, theinter-component prediction may either be performed in the spatial domainand/or spectral domain. An ICP domain indicator in data stream 12 mayvary the domain within which the inter-component prediction hasperformed. The ICP domain indicator may vary the domain at picturesequence, single picture or sub-picture granularity such as, forexample, in units of the aforementioned prediction blocks or in units oftransform blocks in units of which the aforementioned spectraldecomposition is performed.

It will be described later that module 24 may also use inter-componentprediction, namely inter-component prediction on the basis of thereconstructed first component signal 20 as indicated by a dashed branchleading from the output of module 20 to an input of module 24. That is,module 24 would receive a signaled residual signal for the secondcomponent B and could treat the signaled residual signal as a predictionsignal of an ICP prediction from first to second component, i.e. A to B,so as to receive the prediction residual for the intra-componentprediction within component B. The second component signal 26 used bymodule 28 for ICP with respect to the third component C could be theresult of the module's 24 reconstruction on the basis of the signaledresidual signal for component B combined, or not yet combined, with theICP prediction on the basis of the first component signal 22.

As will also be outlined in more detail below, the ICP predictionperformed by module 28 (and optionally by module 24) may be subject toparameterization. This parameterization changes, for example, the ICP ofmodule 28 on the basis of the first and second component signals 22 and26 at sub-picture granularity with respect to, for example, a selectionamong the first component signal 22, the second component signal 26 anda combination thereof, with respect to a weight at which the first andsecond component signals 22 and 26 contribute, in the form of a weightedsum, to the ICP prediction for the third component or the like.Moreover, multiple source ICP signalization in the data stream maysignal the general availability or unavailability of the secondcomponent signal 26 in addition to the first component signal 22 for ICPwithin module 28. The scope of such multiple source ICP signalizationmay relate to a complete video, a single picture or time instant or asequence of pictures or time instances or a slice or a sequence ofslices.

In order to ease the understanding of the various embodiments furtheroutlined below according to which certain possibilities are discussed asto how the ICP of module 28 may be parameterized and varied by arespective signalization in data stream 12, FIG. 2 shows an embodimentof the decoder representing an example of a more specific implementationof the decoder of FIG. 1, namely one where the component signals 22, 26and 30 relate to prediction residuals of intra-component predictionsperformed within the individual decoding branches 32 _(A) to 32 _(C).After explaining FIG. 2, FIGS. 3 and 4 briefly present embodiments ofencoders fitting the embodiments of FIGS. 1 and 2, and then variousimplementations details for tuning the embodiments of FIGS. 1 to 4 aredescribed with respect to the subsequent figures.

FIG. 2 shows a decoder 10 constructed in accordance with FIG. 1 withthree decoding branches 32 _(A) to 32 _(C), wherein in addition tomodules 20, 24 and 28, respectively, each decoding branch comprises anintra-component predictor 34 _(A), 34 _(B) and 34 _(C), respectively anda combiner 36 _(A), 36 _(B), and 36 _(C), respectively, which combinesthe component signal 22, 26 and 30, respectively, output by modules 20,24 and 28, respectively, with the intra-component prediction signaloutput by predictor 34 _(A), 34 _(B) and 34 _(C), respectively. Inparticular, the intra-component predictor 34 _(A) of decoding branch 32_(A) is controlled via intra-component prediction parameters forcomponent A, namely 38 _(A), so as to generate by intra-componentprediction an intra-component prediction signal 40 _(A) which, in turn,is combined by combiner 36 _(A) with the reconstructed first componentsignal 22 so as to result in the reconstructed component A, i.e. thesample values concerning component A of the pictures of the video.Module 20 is fed via data stream 12 with first component residual data42 _(A) signaled, as described above, in spatial or spectral domain, forexample, using entropy coding. Likewise, intra-component predictor 34_(B) is controlled by intra-component prediction parameters forcomponent B, namely 38 _(B), in the data stream 12 so as to definetherefrom a second component intra-component prediction signal 40 _(B)which in turn is combined by combiner 36 _(B) with the reconstructedsecond component signal 26 output by module 24. Module 24 is fed bysecond component residual data 42 _(B), which like residual data 42 _(A)may be present in the data stream 12 in the spatial domain in the formof residual samples or in the form of transform coefficients of aspectral decomposition transform locally applied. In accordance with theembodiment shown in FIG. 2, module 24 is, however, additionallycontrolled via ICP parameter data for the second component, namely 44_(B), present in data stream 12 so as to vary the inter-componentprediction applied by module 24 on the basis of the first componentsignal 22. This option is, as described above, optional and may be leftout. In particular, module 24 internally combines signals 22 and theresidual signal retrieved from data 42 _(B), i.e. the signaled residualsignal for component B, so as to obtain the second component signal 26,which forms the intra-component prediction residual for component B andis, consequently, then combined with the second componentintra-component prediction signal 40 _(B) by combiner 26 _(B) so as toresult in the second component samples of the pictures of the video.

Similar to decoding branch 32 _(B), the intra-component predictor 34_(C) of the third component decoding branch 32 _(C) is controlled viaintra-component prediction parameters 44 _(C) present in data stream 12so as to perform the intra-component prediction and derive theintra-component prediction signal 40 _(C), which in turn is combined bycombiner 26 _(C) with the third component signal 30. Module 28 generatesthe third component signal 30 as the intra-prediction residual on thebasis of third component residual data 42 _(C) in data stream 12 andusing inter-component prediction on the basis of both the first andsecond component signals 22 and 26 with the inter-component predictionof module 28 being controlled via inter-component parameter data for thethird component, namely 44 _(C) in data stream 12. By the combination incombiner 36 _(C), the component C of the pictures in the video results.The combination in combiners 36 _(A) to 36 _(C) may be implemented, asdepicted in FIG. 2, as an addition although other combinations may beused as well, such as, for example, a multiplication.

As announced above, FIGS. 3 and 4 show embodiments of correspondingencoders, i.e. encoders fitting to the decoders shown in FIGS. 1 and 2,respectively. FIG. 3 shows an encoder 100 corresponding to the decoder10 of FIG. 1. The encoder 100 receives the video 16, as depicted in FIG.1, spatially sampled with respect to different components A, B and C inorder to encode same into data stream 12. To this end, encoder 100 isconstructed in a manner corresponding to FIG. 1. Owing to thiscorrespondence, the elements of encoder 100 are referred to usingreference signs which differ from those used with respect to the decodermerely in that 100 is added to the respective reference sign of thecorresponding element in the decoder. Accordingly, the encoder 100 ofFIG. 3 comprises for each of components A, B and C a respective modulefor the respective component, namely modules 120, 124 and 128, whereinmodule 120 is for coding the first component signal 22 into data stream12, module 124 for encoding the second component signal 26 into datastream 12 and module 128 for encoding the third component signal 30 intodata stream 12, wherein module 128 uses inter-component prediction fromthe first and second component signals 22 and 26. Just as describedabove, signals 22, 26 and 30 may represent residual signals, namelyprediction residual signals of an intra-component prediction performedwithin component-specific coding branches 132 _(A), 132 _(B) and 132_(C), respectively.

Accordingly, FIG. 4 shows a more specific embodiment of the encoder ofFIG. 3, corresponding to the decoder of FIG. 2. Correspondingly, encoder100 of FIG. 4 comprises three component-specific coding branches 132_(A), 132 _(B) and 132 _(C), each comprising an intra-componentpredictor 134 _(A,B,C), a residual former 136 _(A,B,C) and therespective module 120, 124 and 128, respectively. As far as theintra-component predictors 134 _(A-C) is concerned, they act in asimilar manner as the respective predictors 34 _(A-C) at the decoderside: they generate, by way of intra-component prediction, therespective intra-component prediction signals 40 _(A), 40 _(B) and 40_(C) on the basis of already encoded portions of the respectivecomponent of video 16 with the difference only residing in relation tothe intra-component prediction parameters 38 _(A-C): while predictors 34_(A-C) are controlled by the latter, predictors 134 _(A-C) adjust thesame in, for example, a rate/distortion optimization sense or the like.The residual formers 136 _(A-C) form the prediction residual between theintra-component prediction signal 40 _(A-C) and the co-located portionof the respective component of video 16 so as to obtain a respectivefirst order component residual signal 120, 124 and 130 which is then ina lossy manner coded into data stream 12 by the respective module 120,124 and 128, respectively. The reconstructible version of the respectivefirst order prediction residual signal 122, i.e. freed from the codingloss introduced by module 120, is signal 22 then used by module 124 as abasis for inter-component prediction so as to encode prediction residualsignal 126 into data stream 12. As an outcome of the encoding, module120 generates the first component residual data 42 _(A), which is theninserted into data stream 12. Likewise, module 124 generates, as anoutcome of the encoding of inbound residual signal 126, second componentresidual data 42 _(B) and ICP parameter data 44 _(B), which is theninserted into data stream 12. On the basis of the latter data, thereconstructible version of residual signal 126 may be derived, i.e. thereconstructible version 26 then used by module 128 for inter-componentprediction along with residual signal 22 for encoding first orderresidual signal 130 into the data stream. As an outcome of the encodingof module 128, module 128 outputs the ICP parameter data 44 _(C) and therespective residual data 42 _(C).

After having described various embodiments of decoders and encoders withrespect to FIGS. 1 to 4, various embodiments are described which relateto various possibilities as to how to adapt the two-source ICPprediction performed by module 28 and 128, respectively. However, beforethat a brief detour is made to H.265/HEVC as an example for a hybridvideo compressing scheme and in order to motivate the advantagesresulting from the two-source ICP prediction However, all statements andthe whole description outlined below should not be treated as beingrestricted to an extension of H.265/HEVC. Rather, the followingdescription merely exemplarily sometimes mentions H.265/HEVC explicitly.

In the case of hybrid video compression schemes like H.265/HEVC, aprediction signal is generated using temporal or spatial or inter-viewprediction (predictive coding) and the resulting prediction, referred toas residual, is then transformed, quantized and transmitted to thedecoder (transform coding). Several entry points for the inter-componentprediction (ICP) are possible. For example, the ICP could be appliedonto the original sample values. With respect to the embodiments ofFIGS. 1 to 4, this means that the source of ICP, namely signals 22 and26, may not necessarily be residuals of intra-component prediction.Rather, they may relate to the original source signal, i.e. video 16,directly, i.e. in the spatial domain, or the ICP is performed on theoriginal signal, i.e. video 16, but in the spectral domain, i.e. withrespect to transform coefficients of a spectral decomposition transform,such as DCT locally applied in units of transform blocks of pictures, ortransform coefficients of a wavelet transform. Due to implementation andapplication efficiency aspects, i.e. in order to improve the same, ICPmay however be performed onto intra-component prediction residualsignals as described and illustrated above with respect to, for example,FIGS. 2 and 4. For such an approach, an affine predictor may be employeddue to complexity reasons. Further simplification leads to a linearpredictor. In the latter case, only the gradient of the predictor mayhave to be transmitted as prediction parameter in the bitstream as partof ICP parameter data 44 _(B) and 44 _(C), respectively. In thefollowing, this parameter is often denoted as α. It is noted here forthe sake of simplification that the following portions of thespecification of the application assume the usage of a linear predictor.The extension of the embodiments outlined further below, however, mayeasily be extended to an affine or more complex predictor.

Using a linear predictor, an ICP approach for residuals could begenerally formulated as:

r′(x, y)=r _(B)(x, y)+α×r ₀(x, y)

In the formula above, r′(x, y) is the final residual sample value forcomponent B at the spatial position (x, y), r_(B)(x, y) thedecoded/signaled residual sample for component B, i.e., extracted fromthe bitstream, a the prediction parameter for component B contained in44 _(B) and r₀(x, y) the reconstructed residual sample of component A atthe same spatial position in the prediction source, e.g., the lumacomponent, wherein r₀(x, y) may be r_(A)(x, y), i.e. the signaledresidual of component A. Please note that α can be a floating pointvalue. For example, see module 24 of the above decoder embodiments.Module 24 could apply ICP in that module 24 uses the residual signal 22as the prediction source r₀, multiplies same using α as signaled withinICP parameter data 44_(B) and adds the signaled residual signal asderived from the residual data 42 _(B), namely r_(B), so as to derivethe inter-component prediction residual signal for component B, i.e. 26,i.e. r′.

Due to implementation aspects, floating point values may be mapped tointeger values. For example, the floating point value α may be allowedto be in the range between −1 and 1, inclusively. Using three bitprecision for the precision, the formula can be rewritten to as follows:

r′(x, y)=r _(B)(x, y)+(α×r ₀(x, y))>>3

The right shift operation is exactly a division by two to the power ofthree. Therefore, the floating pointed α can take the following integervalues.

α ∈ {0,±1, ±2, ±3, ±4, ±5, ±6, ±7, ±8}

Again, due to implementation aspects, α can also restricted to thefollowing values.

α ∈ {0, ±1, ±2, ±4, ±8}

That is, the last mapping allows the decoder, or to be more specificmodule 24, for example, to reconstruct the integer-valued α as followswith α_(d) being the decoded value from the bitstream, i.e. the oneactually comprised within the ICP parameter data 44 _(B) in the datastream 12:

α=1<<α_(d)

The ICP approach explained above representatively with respect to module24, for example, can itself be split into three modules or facets. Thefirst facet specifies the prediction source, the second facet specifiesthe prediction model, the third and the last facet specifies the ICPprediction parameter(s) or, to be more specific, the prediction modelparameter(s). Given the formulas above, the prediction source is thenr₀, the prediction model is the linear predictor using the same spatialposition in the source component as input and the only prediction modelparameter is α.

There is a strong dependency between the second and the thirdfacet/module. An example of such a dependency would be again the simplelinear predictor using the same spatial location in another component,i.e. the prediction source, as the input. In this example, due to thelimitation to the linear predictor using the same spatial location, onlyone prediction (model) parameter is necessitated, and hence only thissingle prediction parameter, i.e. α, needs to be transmitted in thebitstream. There is also an interaction between the prediction sourceand the prediction model. Usually, the luma residuals are taken as theprediction source. This is the case, for example, with respect to module24 in the case of using luma as component A, and a first chromacomponent as component B. However, if all available components are usedas prediction source, an appropriate predictor has to be used, i.e. apredictor that involves samples from both components. This is the casefor module 28. This module has two components available, namelycomponents A and B. Staying at the same example with two predictionsources, i.e. the luma component and the first chroma component ascomponents A and B, for example, the linear predictor would necessitatetwo model parameters instead of one. To be more precise, a linearpredictor which could be used for module 28 may be defined as follows:

r″(x, y)=r _(C)(x, y)+α₀ ×r ₀(x, y)+α₁ ×r ₁(x, y).

That is, as far as module 28 is concerned, two prediction sources areavailable, namely signals 22 and 26. The signal 22 is r₀ and the signal26 is r₁. That is, for ICP module 28 has available the co-locatedportions of signals 22 and 26 for ICP of a currently ICP predictedportion of signal 30, i.e. r′. In particular, module 28 uses a weightedsum of these co-located portions, namely signal 22 weighted by α₀ andsignal 26 weighted by α₁, with the weighted sum being corrected byaddition of the signaled residual as obtained from the residual data 42_(C), namely r_(C).

As far as the relation between modules 28 and 24 is concerned, thefollowing shall be noted. As depicted by the continuous lines in FIGS. 2and 4, module 24 may use ICP on the basis of first component signal 22and the second component signal 26 is obtained by ICP prediction andcombination with the transmitted second component residual data 42 _(B),i.e. r′ may serve as a basis, i.e. one prediction source, of the ICPperformed by module 28, i.e. r′ may be used as r₁. But as has also beendescribed above, in accordance with an alternative, module 24 does notuse ICP. In that case, in FIGS. 2 and 4 the connection between module's20 output on the one hand and module 24 on the other hand would be leftout (or between module 120 and 124 ). In that case, r₁ would be r_(B).In accordance with a further embodiment, the embodiments of FIGS. 2 and4 could be modified in that r₁ is chosen to be equal to re despitemodule 26 using ICP on the basis of component A. In that case, the arrowleading from module 24 to module 28 in FIG. 2 would start from a furtheroutput of module 24 other than the output leading to the combiner 36_(B).

Thus, in accordance with the embodiments outlined above, the possibilityis provided to use multiple prediction sources for ICP, wherein theoperation characteristics of the ICP approach are further extended inorder to achieve higher compression efficiency. In the following,various details are presented with respect to the rather generalmultiple prediction source ICP described up to now. The followingdescription first deals with the a possible global signaling of themultiple source ICP. Then, the local signaling of the multiple sourceICP in accordance with various embodiments is dealt with. Then,additional dependencies for the multiple source ICP and furthertechniques enabling higher efficiency for the image and videocompression application are described.

A kind of global signaling of multiple sources for ICP involves thepossibility that the multiple source ICP approach can be turned on oroff. When the multiple source ICP is enabled using a global flagtransmitted in an appropriate level, an additional bit or a series ofbits is transmitted, for example, for each transform block, or eachprediction unit, or coding unit, signaling its usage. The global flagrepresents a kind of multiple source ICP signalization in the datastream switching between various ICP coding modes of a set of ICP codingmodes including a multiple source ICP coding mode and at least onenon-ICP coding mode. There may be various multiple source ICP codingmodes as well, differing, for example, in adjustability of the ICPdomain, i.e. spatial or spectral domain, and so forth. Accordingly, theglobal flag could be a single bit or a series of bits specifying furtherthe prediction model in terms of one or more prediction parameters. The“additional bit or a series of bits transmitted for each transformblock, or each prediction unit, or coding unit” in case of multiplesource ICP being enabled, is an example for the aforementioned ICPparameter data 44 _(C).

The global flag may be transmitted in a sequence parameter set, such asthe sequence parameter set of H.265/HEVC, or in the picture parameterset, or even in the slice header. The granularity depends on the usageof additional tools, e.g. for tiles or wavefront processing, both forparallel processing, and even the signaling in different levels ispossible. For example, the multiple source ICP could be enabled for thewhole video sequence, but there could be a disablement for a specificcontent in the sequence. Given such an example, the global flag in thepicture parameter set would override the flag in the sequence parameterset, for example.

Thus, to summarize, in accordance with an embodiment, the decoder 10could be configured to be responsive to a multiple source ICPsignalization 200 inserted into data stream 12 by encoder 100 so as toswitch, for different ICP mode portions 202 of the multi-component video16, between ICP coding modes of a set of ICP coding modes including amultiple source ICP coding mode and a non-ICP coding mode.

In accordance with the multi-source ICP coding mode, inter-componentprediction is performed on the basis of a signaled one of spatiallycorresponding portions 204 and 206 of the first and second componentsignals 22 and 26 of the components A and B with the signalization beingdone explicitly or implicitly within data stream 12. Alternatively, themultiple source ICP coding mode involves inter-component predicting thethird component signal 30 of component C on the basis of a combinationsuch as a weighted sum, of spatially corresponding portions 204 and 206.To be more precise, imagine that the multiple source ICP signalization200 of FIG. 5a signals for the middle ICP mode portion of video 16 thatmultiple source ICP coding mode is enabled. In that case, modules 28 and128, respectively, could perform ICP for component C block-wise in, forexample, units of blocks 208, which may be, for example, predictionblocks or the like, wherein the ICP parameter data 44 _(C) indicates forthese blocks 208 whether the respective block 208 is inter-componentpredicted from spatially corresponding portion 204 orspatially-corresponding portion 206. Alternatively, in blocks 208 ofpictures within middle portion 202, the third component signal 30 ispredicted from a combination of both portions 204 and 206. ICP parameterdata 44 _(C) may then indicate the manner in which each portion 208 isinter-component predicted from co-located portions 204 and 206 in termsof, for example, weighting factors α₀ and α₁ indicating the weights ofthe weighted sum of portions 204 and 206 yielding the inter-componentpredictor for the respective block 208.

In the non-ICP coding mode, inter-component prediction may not beavailable for the respective ICP mode portion 202. Accordingly, for suchan ICP mode portion, no ICP parameter data 44 _(C) needs to be presentin the data stream 12. Alternatively, for such an ICP mode portion 202,inter-component prediction may be performed by modules 28 and 128,respectively, from a fixed one of components A and B. For example,blocks 208 of such a non-ICP coding mode portion 202 may be ICPpredicted from the co-located block 204 of component A or all blocks 208may alternatively be inter-component predicted from co-located block206, but a switching between blocks 208 is not feasible, i.e. either allblocks 208 within portion 202 are inter-component predicted from blocks204 of component A or all blocks 208 within portion 202 areinter-component predicted from respective co-located block 206 ofcomponent B.

As already stated above, ICP mode portions 202 may be picture sequences,individual pictures, or slices or a sequence of slices. As indicatedabove, for ICP mode portions 202 for which the multiple source ICPcoding mode is enabled, the ICP parameter data 44 _(C) comprises, forexample, two weights α₀ and α₁ for portions 208, while for ICP modeportions 202 for which the non-ICP coding mode is active, either no ICPparameter data 44 _(C) is present, or the ICP parameter data 44 _(C)signals for blocks 208 merely one of weights α₀ and α₁ with the otherbeing set to zero for all blocks 208 within the respective portion 202.

Several possibilities exist for the local signaling of multiple sourcesfor ICP. For example, if multiple sources ICP is used, a decision 210for the prediction source may be transmitted locally as part of the ICPdata 44 _(C) as can be seen in FIG. 5b . For example, components A, Band C may be luma, first chroma and second chroma, for example. Then,the ICP parameter data 44 _(C) may comprise a 210 flag indicating for arespective block 208 whether the source for inter-component predictionis luma, i.e. A, or the first chroma component, i.e. B. The blocks 208may be coding blocks, prediction blocks or transform blocks. Codingblocks are, for example, blocks at which the intra-component predictionparameters 38 _(C) switch between spatial and temporal prediction.Prediction blocks may be blocks at which the intra-component predictionparameters 38 _(C) signal or vary the prediction parameters associatedwith the sort of prediction signaled for the coding block which therespective prediction block is part of. For example, if spatialprediction is signaled for the coding block, the prediction parametersfor the prediction block or prediction blocks of that coding block maysignal a spatial direction along which the respective prediction blockis to be spatially predicted from neighboring already decoding/encodedportions of component C, and in case of a temporal prediction mode beingsignaled for the coding block to which the respective prediction blockbelongs, the prediction block may signal a motion vector as predictionparameter. Transform blocks may be blocks at which the intra-componentprediction residual for component C is spectrally decomposed. In thisregard, it should be noted that a flag 210 indicating whether the sourcefor prediction is luma or first chroma component could be coupled orindependent from other ICP prediction parameters 212, such as forexample the prediction weight a, which is used as α₀ in the case ofcomponent A forming the ICP prediction source, and as +₁ in the case ofcomponent B forming the ICP prediction source. The case of dependency isgiven, for example, when the prediction source is signaled after theprediction parameter(s), such as the weight. On the other hand, theindependent case may be given when the source is signaled by way of flag210 for a prediction block or a coding block but the ICP predictionparameters 212 are transmitted for each transform block.

Given the example above, the flag 210 indicating the prediction sourcemay be transmitted only for blocks 208 of component C, such as, forexample, only for transform blocks of the second chroma component. Itmay be that the ICP prediction source is signaled for a block 208 aspart of the ICP parameter data 44 _(C) only in case of the ICPprediction weight α for block 208 is signaled within the ICP parameterdata 44 _(C) as not being equal to zero, meaning that ICP predictionshould be performed for block 208 of component C. There are twosituations where the condition for multiple source are given. The firstcase occurs when the respective transform blocks of the first component,such as the luma component, and the second component, such as the firstchroma component, inherit residuals. The second case is given when theluma transform block inherits residuals while the first chroma componentconsists of zero-valued residual values only, but it is predicted fromthe luma transform block.

For the flag 210 indicating the ICP prediction source, a fixed contextmodel could be applied. A dependency on the situation where multiplesources occur is also possible resulting in two different contextmodels. Furthermore, there could be a dependency on other ICP predictionparameter(s) 212, such as the weight. For example, a negative a mayresult in a different context model than a positive α. Anotherpossibility is the dependency on the absolute value of α. In thisexample, an absolute a larger than two would result in the usage of adifferent context model than the case where α is equal or smaller thantwo.

Accordingly, see for example FIG. 6, which illustrates an embodimentwhere the ICP prediction data 44 _(C) indicates for a respective block208 of component C a weight a as the ICP parameter 212, conditionallyfollowed by an ICP source indicator 210. Accordingly, in accordance withFIG. 6, module 28 and 128, respectively, reads/writes a from/to the ICPparameter data 44 _(C) in step 220 and if a check 222 whether α is equalto zero reveals that α is actually zero, then the ICP parameter data 44_(C) comprises for this block 208 no further ICP parameter data and noICP is performed for block 208 on the basis of any of components A and Bas indicated at 224. However, if α is non-zero, then the ICP parameterdata 44 _(C) comprises or signals for block 208 the ICP predictionsource by way of a source flag 212 which is read from or written to theICP parameter data 44 _(C) in step 226 or 228.

For illustration purposes, FIG. 6 illustrates the possibility wheredifferent contexts are used for entropy encoding/decoding the sourceflag depending on whether α of step 220 fulfills a predeterminedcriterion or not, which circumstance is checked at 229. As outlinedabove, the criterion may be fulfilled if the absolute value of a isgreater than α predetermined value such as two, or whether α is negativeor the like. However, as already denoted above, the dependency of thecontext used to decode/encode the source flag on α is merely optional,and accordingly steps 229 and 228 may be left out in accordance with analternative embodiment. Irrespective of whether step 226 or 228 applies,in the case of α being unequal to zero, the ICP is performed using α ofstep 220 as α₀ in the case of ICP prediction source being the firstcomponent A, or α₁ in case of the ICP prediction source indicated by thesource flag being the second component B in step 230.

Thus, summarizing FIG. 6, the ICP parameter data 44 _(C) may have oneweight a coded into the data stream 12 for each block 208, i.e. 212. Thecoding/decoding in step 220 may involve spatial prediction on the basisof α of a neighboring block. Further, the ICP parameter data 44 _(C) mayhave a source flag 210 coded into data stream 12 for block 208 dependingon the value of α for this block 208 wherein the coding may compriseentropy coding, and in particular context-adaptive entropy coding usinga context which depends on a for this current block 208. Accordingly,steps 226 and 228 may involve context-adaptive entropy coding/decoding.Step 230 involves the appliance of the above identified formulaecomprising α₀ and α₁. α of step 220 is used as α₀ or α₁ depending on theICP's source signaled by the source flag. The other of α₀ and α₁ is setto be zero, for example.

Extended ICP techniques are described next. In particular, when multiplesources are available as in the case of component C, a possible ICPpredictor may accept both components for prediction, i.e. components Aand B. In the case of using a linear ICP predictor, the ICP predictionparameters 212 would have to specify the weight of ICP prediction twicewith the outcome or result of each component being linearly combined asdescribed above.

FIGS. 5c and 7 illustrate the possibility according to which the ICPparameter data 44 _(C) comprises or signals two weights α₀ and α₁ foreach block 208 which are read/written in steps 232 and 234,respectively, with the same being applied at step 236 in accordance withthe above identified formula.

For sake of completeness, FIG. 5d-5g show the circumstance which hasalready mentioned above, namely that the ICP of module 28 may beperformed in the spectral domain or in the spatial domain with thesignaled component C residual signal signaled in 42 _(C) in the spectraldomain, i.e. in form of transform coefficients such as DCT coefficientsor other transform coefficients of transform blocks or the like.Performing multiple source ICP in the spatial domain is illustrated inFIGS. 5d and 5e using module's 28 embodiment of FIGS. 5b and 5c as abasis, respectively. As is shown, signals 24 and 22 arrive in form ofspatially corresponding, i.e. co-located, samples, are multiplied byweights α₀ and α₁, respectively, and summed up with the respective, i.e.collocated, samples as obtained by an inverse transform applied onto thearriving transform coefficients 42 _(C) so as to yield signal 30.Performing multiple source ICP in the spectral domain is illustrated inFIGS. 5f and 5g again using module's 28 embodiment of FIGS. 5b and 5c asa basis, respectively. As is shown here, signals 24 and 22 may arrive inform of spatially corresponding, i.e. co-located, samples in which casethey may be subject to a (forward) transform 217 so as to obtain aspectral decomposition of the same, i.e. transform coefficients.Alternatively, signals 20 and 24 already arrive in the transform domain.A transform 217 may be necessitated, for example, in case ofmiss-alignment of transform blocks between component A and C and B andC, respectively. The coefficients of signals 20 and 24 are multiplied byweights α₀ and α₁, respectively, and summed up with the respective, i.e.spectrally corresponding, coefficients as obtained from 42 _(C). Thesummed-up coefficients are then subject to the inverse transform 216 soas to yield signal 30.

A further approach to improve the compression efficiency is the exchangeof components for ICP. According to this approach, a syntax element maybe signaled within the ICP parameter data 44 _(C), specifying thecorrect order of the residuals. In this example, three transform blocksare, for example, reconstructed for a spatially corresponding portion,one for each component A, B and C, and ICP may be employed. Then, thesyntax element specifies that the second and the third residual blocksbelonging to second and third component residual data 42 _(B) and 42_(C) are swapped. It would also be possible to exchange the first andthe second component or even the first and the third component. Thisadaptive component switch, especially meaningful in the combination withICP and multiple source ICP, allows the reduction of the energy withless prelude costs. For example, the application is allowed to switchthe two chroma components B and C. In this example, the prediction ofthe two chroma components B and C from luma, i.e. component A, wouldresult in the same costs. However, the prediction of the second chromacomponent using the first chroma component would necessitate moreoverhead, but the prediction of the first chroma component using thesecond chroma component necessitates less bits and results in lowercosts. In such a case, a swap of the two chroma transform blocks wouldfurther reduce the total costs resulting in a higher compressionefficiency.

This is depicted again in FIG. 8. FIG. 8 shows the first, second andthird component residual data 42 _(A) to 42 _(C) being read/written insteps 240, 242 and 244, respectively, wherein the ICP by modules 24 and28 and 124 and 128, respectively, namely 246, is controlled by the ICPparameter data 44 _(B) and 44 _(C) including a swap signalization 248, aweight for the ICP to be performed on the basis of the first component,namely a, which is taken from the ICP parameter data 44 _(B) for thesecond component and a weight to be used for the ICP between the secondand third components, namely α₁ which is taken from the ICP parameterdata 44 _(C) for the third component. Depending on the swapsignalization, the transmitted residual signals 42 _(A) to 42 _(C) areeither combined in the ICP 246 according to the continuous lines or thedashed lines. As can be seen, the second component signal 26 is eitherobtained by ICP on the basis of the first component or the thirdcomponent depending on the swap signalization, and likewise the thirdcomponent signal 30 is either obtained by ICP on the basis of the firstcomponent or the second component, respectively. In the non-swapped caseillustrated by the continuous lines, ICP parameter data weights α and α₁remain their meaning, i.e. they control the ICP prediction of the secondcomponent signal 26 and third component signal 30, respectively, but inthe swapped case, indicated by the dashed lines, the ICP parameter dataweights α and α₁ are re-interpreted as controlling the first stage andsecond stage ICP prediction, respectively: ICP parameter data weight arefers to the first stage ICP and ICP parameter data weight α₁ refers tothe first stage ICP. If not swapped, the re-interpretation does notchange anything, but in the swapped case, the third component signal 30is inter-component predicted before the second component signal 26, sothat ICP parameter data weight α₁ is now actually used forinter-component predicting second component signal 26. In other words,in the swapped condition, the second component B preliminarily assumesthe role of the third component C and vice-versa, as far asinter-component prediction is concerned.

It is noted that the embodiment of FIG. 8 may be combined with theprevious ones in that the ICP parameter data weight α₁ of data 44 _(C)may be accompanied with further data such as ICP parameter data weightα₀ or source indicator 212: As data 44 _(C) is re-interpreted to referto the second stage ICP, i.e. to the second component the signal ofwhich is subject to ICP—whether this is signal 26 or 30—two sources areavailable in both cases irrespective of the swap signalization 248, andICP parameter data weight α₀ could be used to control the ICP on thebasis of component A in both cases and the source indicator could beinterpreted as switching between components A and B in the non-swappedcase and between components A and C in the swapped case, respectively.

Further, in a manner similar to FIG. 8, it would be feasible to changethe aforementioned switching flag into a flag signaling a color spacechange i.e. switching between color spaces: for each component, the ICPprediction parameter α₀ or α₁ is transmitted, locally changing asdescribed above; further, color domain change flag locally indicateswhether the color domain is to be changed or not. If not changed, bothsecond and third components B and C, for example, are individuallypredicted from A using α₀ or α₁ so as to reveal the two chromacomponents, respectively, and component A is treated as luma just asdescribed above. If color change is signaled to take place, however, Band C, for example, are individually predicted from A using α₀ or α₁,respectively, but they are then commonly subject to a color space changetransformation which, for example, linearly transfers the ABC colorspace into the YCC color space. While component B, for example, ispredicted from A only in case of no color space change, it is, forexample, effectively predicted from A and C in case of color spacechange. Even alternatively, two or more types of color changetransformations mapping the signaled color space ABC to the YCC colorspace may be available and switched between by way of signalization 248.Thus, in locally varying manner, the color space in which the ABCcomponents are transmitted, may change between two or more color spaces,and so the transformation to YCC does change between no transformationand color transformation as signaled by signalization 248. Signalization248 may be transmitted in the data stream in units such as coding units,greater than or equal to units at which the ICP prediction praramatertransmission takes place, such as transform blocks. Thus, α₀ or α₁,would be transmitted for components B and C at first blocks such astransform blocks, the residual r_(B) transmitted for B would be combinedwith the residual r_(A) transmitted for component A according tor_(B)′=r_(B)+α₀·r_(A) and likewise, the residual r_(C) transmitted for Cwould be combined with the residual r_(A) according tor_(B)′=r_(B)+α₁·r_(A), and the prediction residual signal (22, 26, 30)would finally obtained either by a color transformation which may besimilar to a RGB to YCC color transform, denoted T for simplicity, or bydirectly adopting the residuals as the YCC prediction residual signal,i.e. either (r_(Y),r_(C1),r_(C2))^(T)=T·(r_(A), r_(B)′,r_(C)′)^(T) or(r_(Y),r_(C1),r_(C2))^(T)=(r_(A), r_(B)′,r_(C′))^(T), respectively.Whether color space transform T is applied or not is controlled viasignalization 248. T may be

$\begin{pmatrix}1 & 1 & 0 \\1 & {- 1} & {- 1} \\1 & {- 1} & 1\end{pmatrix},$

for example.

The coding of the ICP prediction parameter α, or α₀ or α₁ in data 44_(B) or 44 _(C) mentioned above can be coded using the signaling of theinteger nominator of the fractional value of the weight as describedabove, or can be even further improved. When ICP is applied in theR′G′B′ colour space, the value of α (representatively used for any of α,or α₀ or α₁) is mainly positive and relatively large, i.e., 1 or 0.5 infloating point precision. On the other hand, for Y′C_(b)C_(r), thevalues of α is often centred on the zero value and is relatively small.An asymmetrical mapping and limitation of α can be employed in order tofurther improve the efficiency in terms of compression ratio. Given theobservation, the α mapping can be as follows.

α ∈ {0, ±1, ±2, ±4, ±8} or α ∈ {0, ±1, ±2, ±4, +8}

Please note that, in order distinguish the maximum allowed value of α,the sign of a should be transmitted first in the bitstream. In the caseof symmetrical mapping the order is irrelevant, i.e., the sign can betransmitted after the transmission of the absolute value of α. Moreover,the absolute value of α could be coded/decode by entropy coding usingcontext-modeling depending on the sign of α so as to account for thedifferent probability distribution for the frequency of occurrance ofpositive and negative values of α.

In the following, some embodiments are discussed even more specifically.

In accordance with an embodiment, for example, in the case of twoprediction sources as it was the case in the embodiments presentedabove, a flag 210, called source flag in FIG. 6 above, is transmittedafter the specification of the ICP prediction parameter 212 and thisflag 210 indicates which predictions source should be employed. Notethat for this embodiment, the prediction source flag 210 is onlynecessitated when the prediction should be applied, which can be derivedfrom the ICP prediction parameter.

In a further embodiment, independently from the specific ICP predictionparameter 212 of the respective block 208, such as the respective nestedtransform blocks in a prediction block, the source flag 210 indicatingwhich prediction source should be employed is transmitted for eachprediction unit. It should be noted that it is also possible to transmitthe ICP prediction parameters 212 such as α in the prediction blocklevel in this embodiment.

In another embodiment of the invention, independently from the specificprediction parameters of the nested transform blocks in a coding block,the flag indicating which prediction source should be employed, i.e.source flag, is transmitted for each coding block. It should be notedthat it is also possible to transmit the ICP prediction parameters inthe prediction block level or coding block level in this embodiment.

FIG. 9 illustrates the just outlined possibilities illustratively. Inparticular, as described above, the ICP parameter data 44 _(C) maycomprise two components, namely ICP prediction parameter 212 such as aweight a and an unconditionally coded ICP source flag 210. Other thandepicted in FIG. 6, steps 226, 228 and 229 would be rearranged to bepositioned between steps 220 and 222, wherein, as already outlinedabove, steps 228 and 229 may even be left out. In any case, FIG. 9illustrates the possibility that the granularity at which the ICPparameter data 44 _(C) signals the ICP prediction source is coarser thanthe granularity at which the ICP prediction parameter α is transmitted.In particular, while the ICP source flag is transmitted in units ofblocks 250, indicated by continuous lines in FIG. 9, the ICP predictionparameter α is indicated in the ICP prediction parameter data 44 _(C) inunits of sub-blocks 252, i.e. sub-partitions of blocks 250. While FIG. 9illustrates blocks 250 and 252 of picture 18 to be rectangular, itshould be noted that blocks of other shapes may be used as well.

In a further embodiment, the source flag 210 indicating the predictionsource may be coupled to the respective ICP prediction parameter(s) 212,such as the weight, i.e. the ICP prediction parameter(s) specified forthe current transform block or the current prediction block or even thecurrent coding block. In this embodiment, the source flag 210 indicatingthe prediction source may be coded only if the only prediction parameterin the case of a linear prediction is in the range of −0.25 and +0.25(or −2 and +2 for the integer valued α—or to be more precise, theinteger valued nominator thereof), but inclusively. For example, seeFIG. 6. Here, the ICP parameter or data 44 _(C) necessitates thedecoding of the source flag only in case of a being unequal to zero.Additionally, or alternatively, the source flag may be comprised by theICP parameter data 44 _(C) for a certain block only in case of α beingin a certain value range, such as between −0.25 and +0.25, bothinclusively, mentioned above. If α is outside that range, the sourceflag would not be explicitly transmitted within the data stream, but forexample inferred to refer to the first component A, for example, as theICP prediction source. For example, if component A is the luma componentand components B and C are two chroma components, then a large absolutevalue of α is a hint that the predictions source for the second chromacomponent C is the luma component rather than the other first chromacomponent B. Thus, in FIG. 6 a further check would be positioned between222 and 229 checking whether or not a is within the value rangenecessitating the transmission/reading of the source flag. If not, nosource flag is read/written, otherwise step 229 is visited.

In another embodiment, the source flag indicating the prediction sourceis coupled to the ICP prediction parameter(s) of the first chromacomponent. In this embodiment, the source flag of ICP parameter data 44_(C) indicating the prediction source is, for example, coded/decodedonly if the only ICP prediction parameter in the case of a linearpredictor for the co-located block in the ICP parameter data 44 _(B),i.e. α, is between −0.25 and +0-25 or −2 and +2 for the integer value α,both inclusively, when the value range may also be chosen differently.For example, a check could be added to FIG. 7, according to which it ischecked whether the ICP parameter data 44 _(B) indicates for thec-located block that the inter-component prediction of component B fromthe respective co-located block is performed using a weight α, themagnitude of which is, for example, above some predetermined value. Ifso, this may be used as a hint that the components A, B and C correspondto a YCC like color space in which case the third component C shouldmost likely be ICP predicted on the basis of the second component, i.e.the putative first chroma component, so that in that case the sourceflag is inferred to identify the second component as ICP predictionsource. If, however, the magnitude of α for the co-located block asindicated by the ICP prediction parameter data 44 _(B) is smaller thanthe predetermined value, then the source flag is signaled as part of theICP parameter data 44 _(C) for the current block.

In accordance with an embodiment, the context model for the flagindicating the prediction source is independent from the ICP predictionparameter such as the weight. Consequently, one fixed context model isemployed. This means, for example, that regarding the description ofFIG. 6, steps 228 and 229 may be left out with the yes-path of check 222leading directly to 226.

In another embodiment, however, the context model for the source flagdepends on the ICP prediction parameter(s), such as the weight. When thelinear predictor is employed, a different context model may, forexample, be used if the only prediction parameter, namely the weight, isin the range between, for example, −2 and 2, both inclusively, in thecase of an integer-valued prediction parameter as discussed above.

Further, a different context model may be used if the only ICPprediction parameter in the case of a linear predictor is negative. Thishas also been discussed above.

The usage of multiple prediction sources may be turned on and off usinga flag transmitted in the sequence parameter set, for example, as hasbeen discussed above with respect to FIG. 5. The transmission may,however, also take place in the picture parameter set or in the sliceheader.

The usage of multiple prediction sources can be specified in differenthierarchical levels. For example, it can be specified in the sequenceparameter set and the picture parameter set. Because the pictureparameter set flag is lower, this embodiment enables the possibility todisable the multiple source ICP for a picture or a frame of the videosequence. In a further embodiment, the flag indicating the predictionsource, i.e. the source flag, may depend on the relative differencebetween the ICP prediction parameter, i.e. the weight, for the currentcomponent and the ICP prediction parameter, such as the weight, for theprevious component. If the relative difference is greater than a givenlimit, the flag is derived to be equal to one, for example. In otherwords, in case of FIG. 6, an additional check may be applied downstreamcheck 222, wherein it is checked in this additional check whether theweight associated with the co-located block according to the ICPparameter data 44 _(B) differs from α of the ICP parameter data 44 _(C)for the current block by more than a predetermined amount. If yes, thismay be interpreted as a hint that components A to C are related eachother like a YCC color space and that accordingly the source flag may beinferred to identify the putative first chroma component, i.e. componentB, as the ICP source for the ICP of component C. Otherwise, thereading/writing of the source flag is performed. In other words,responsive to ICP prediction parameter signalization 212 of data 44_(C), the third-component prediction parameter α may vary at sub-picturegranularity, and likewise, responsive to ICP prediction parametersignalization for the second component signal in data 44 _(B), acomponent-signal prediction parameter α varies at sub-picturegranularity. Thus, the weights may vary locally between ICP forcomponent B and multi-source ICP for component C. Thus, a check may beperformed as to where the second-component and third-componentprediction parameter differ by more than a predetermined limit, forexample sing a difference or quotient of the a values as a measure ofthe deviation. For locations where they do not differ by more than thelimit, the ICP source indicator 210 may be present in data 44 _(C) whilefor locations where the limit is exceeded, the ICP source indicator 210may be otherwise inferred as described above.

In accordance with a further embodiment, when multiple prediction sourceare available, the ICP prediction parameter(s) are transmitted twicespecifying a predictor supporting a weighted combination of theprediction source, as has been outlined above with respect to FIG. 7.

In accordance with a further embodiment, a linear predictor is employedfor multiple source ICP and the ICP prediction parameter is quantized.In this embodiment, the only absolute ICP prediction parameter isbinarized using truncated unary code and coded and the sign istransmitted separately. The sign may be coded first and depending on thesign of the only prediction parameter, different context models may beused for the bins of the binary decomposition. In accordance with afurther embodiment, the sign is coded first, and then depending on thecoded sign, the quantization of the prediction parameter is performeddifferently, In this embodiment, the maximum allowed predictionparameters may be in the range between 0.25 and 1, both inclusively.

In accordance with an embodiment, a flag may indicate whether the secondand the third component are exchanged. This has been outlined above withrespect to FIG. 8. In this embodiment, the residuals constructed for therelated transform block of the first chroma component may be treated asthe residuals for the second component and vice versa. With respect toabove description of certain embodiments it is noted that same areeasily transferable to multi-component picture coding.

Although some aspects have been described in the context of anapparatus, it is clear that these aspects also represent a descriptionof the corresponding method, where a block or device corresponds to amethod step or a feature of a method step. Analogously, aspectsdescribed in the context of a method step also represent a descriptionof a corresponding block or item or feature of a correspondingapparatus. Some or all of the method steps may be executed by (or using)a hardware apparatus, like for example, a microprocessor, a programmablecomputer or an electronic circuit. In some embodiments, some one or moreof the most important method steps may be executed by such an apparatus.

The inventive encoded picture or video signal can be stored on a digitalstorage medium or can be transmitted on a transmission medium such as awireless transmission medium or a wired transmission medium such as theInternet.

Depending on certain implementation requirements, embodiments of theinvention can be implemented in hardware or in software. Theimplementation can be performed using a digital storage medium, forexample a floppy disk, a DVD, a Blu-Ray, a CD, a ROM, a PROM, an EPROM,an EEPROM or a FLASH memory, having electronically readable controlsignals stored thereon, which cooperate (or are capable of cooperating)with a programmable computer system such that the respective method isperformed. Therefore, the digital storage medium may be computerreadable.

Some embodiments according to the invention comprise a data carrierhaving electronically readable control signals, which are capable ofcooperating with a programmable computer system, such that one of themethods described herein is performed.

Generally, embodiments of the present invention can be implemented as acomputer program product with a program code, the program code beingoperative for performing one of the methods when the computer programproduct runs on a computer. The program code may for example be storedon a machine readable carrier.

Other embodiments comprise the computer program for performing one ofthe methods described herein, stored on a machine readable carrier.

In other words, an embodiment of the inventive method is, therefore, acomputer program having a program code for performing one of the methodsdescribed herein, when the computer program runs on a computer.

A further embodiment of the inventive methods is, therefore, a datacarrier (or a digital storage medium, or a computer-readable medium)comprising, recorded thereon, the computer program for performing one ofthe methods described herein. The data carrier, the digital storagemedium or the recorded medium are typically tangible and/ornon-transitionary.

A further embodiment of the inventive method is, therefore, a datastream or a sequence of signals representing the computer program forperforming one of the methods described herein. The data stream or thesequence of signals may for example be configured to be transferred viaa data communication connection, for example via the Internet.

A further embodiment comprises a processing means, for example acomputer, or a programmable logic device, configured to or adapted toperform one of the methods described herein.

A further embodiment comprises a computer having installed thereon thecomputer program for performing one of the methods described herein.

A further embodiment according to the invention comprises an apparatusor a system configured to transfer (for example, electronically oroptically) a computer program for performing one of the methodsdescribed herein to a receiver. The receiver may, for example, be acomputer, a mobile device, a memory device or the like. The apparatus orsystem may, for example, comprise a file server for transferring thecomputer program to the receiver.

In some embodiments, a programmable logic device (for example a fieldprogrammable gate array) may be used to perform some or all of thefunctionalities of the methods described herein. In some embodiments, afield programmable gate array may cooperate with a microprocessor inorder to perform one of the methods described herein. Generally, themethods are performed by any hardware apparatus.

The apparatus described herein may be implemented using a hardwareapparatus, or using a computer, or using a combination of a hardwareapparatus and a computer.

The methods described herein may be performed using a hardwareapparatus, or using a computer, or using a combination of a hardwareapparatus and a computer.

While this invention has been described in terms of several advantageousembodiments, there are alterations, permutations, and equivalents whichfall within the scope of this invention. It should also be noted thatthere are many alternative ways of implementing the methods andcompositions of the present invention. It is therefore intended that thefollowing appended claims be interpreted as including all suchalterations, permutations, and equivalents as fall within the truespirit and scope of the present invention.

1. Decoder configured to decode a multi-component picture or videospatially sampling a scene with respect to different components, byreconstructing a first component signal relating to a first component ofthe multi-component picture or video from a data stream; reconstructinga second component signal relating to a second component of themulti-component picture or video from the data stream; reconstructing athird component signal relating to a third component of themulti-component picture or video using inter-component prediction fromthe reconstructed first component signal and the reconstructed secondcomponent signal.
 2. Decoder according to claim 1, wherein the decoderis configured to be responsive to a multiple-source ICP signalization inthe data stream so as to switch, for different ICP mode portions of themulti-component picture or video, between ICP coding modes of a set ofICP coding modes comprising a multiple-source ICP coding mode in whichthe decoder is configured to reconstruct the third component signal in acurrent sub-portion of a current picture of the multi-component pictureor video using inter-component prediction from a signaled one of, or acombination of, spatially corresponding portions of the reconstructedfirst component signal and the reconstructed second component signal andat least one of a non-ICP coding mode in which the decoder is configuredto reconstruct the third component signal in a current sub-portion ofthe current picture of the multi-component picture or video not usingany inter-component prediction and a fixed-one-source ICP coding mode inwhich the decoder is configured to reconstruct the third componentsignal in the current sub-portion of the current picture of themulti-component picture or video using inter-component prediction fromspatially corresponding portions of a fixed one of the reconstructedfirst component signal and the reconstructed second component signal,which is fixed within each portion of the multi-component picture orvideo for which the decoder, in response to the multiple-source ICPsignalization, switches to the fixed-one-source ICP coding mode. 3.Decoder according to claim 2, wherein the multiple-source ICPsignalization is signaled in the data stream such that the ICP modeportions are single pictures, picture sequences or slices.
 4. Decoderaccording to claim 1, wherein the first component is a luma, the secondcomponent is a first chroma component, and the third component is asecond chroma component.
 5. Decoder according to claim 1, wherein thedecoder is configured to switch, at a first sub-picture granularity,between reconstructing the third component signal in a current pictureof the multi-component picture or video using inter-component predictionfrom a spatially corresponding portion of the reconstructed firstcomponent signal and reconstructing the third component signal in thecurrent picture of the multi-component video using inter-componentprediction from a spatially corresponding portion of the reconstructedsecond component signal.
 6. Decoder according to claim 5, wherein thedecoder is configured to switch, at the first sub-picture granularity,between reconstructing the third component signal in the current pictureof the multi-component picture or video using inter-component predictionfrom a spatially corresponding portion of the reconstructed firstcomponent signal and reconstructing the third component signal in thecurrent picture of the multi-component picture or video usinginter-component prediction from a spatially corresponding portion of thereconstructed second component signal responsive to an explicit ICPsource signalization in the data stream.
 7. Decoder according to claim5, wherein the decoder is configured to perform the reconstruction ofthe third component signal relating to the third component of themulti-component picture or video using spatial, temporal and/orinter-view prediction with switching between spatial, temporal and/orinter-view prediction modes in units of prediction blocks, wherein thedecoder is configured such that the first sub-picture granularitysubdivides the current picture in units of prediction blocks.
 8. Decoderaccording to claim 5, wherein the decoder is configured to perform thereconstruction of the third component signal relating to a thirdcomponent of the multi-component picture or video using spatial,temporal and/or inter-view prediction and by inverse-transforming aprediction residual of the spatial, temporal and/or inter-viewprediction in units of transform blocks, wherein the decoder isconfigured such that the first sub-picture granularity subdivides thecurrent picture in units of transform blocks.
 9. Decoder according toclaim 1, wherein the decoder is configured to perform theinter-component prediction from the reconstructed first component signaland the reconstructed second component signal using linear predictionwith varying, responsive to ICP prediction parameter signalization inthe data stream, weights at which the reconstructed first componentsignal and the reconstructed second component signal linearly contributeto the inter-component prediction at a second sub-picture granularity.10. Decoder according to claim 1, wherein the decoder is configured toperform the reconstruction of the third component signal relating to athird component of the multi-component picture or video using spatial,temporal and/or inter-view prediction with switching between spatial,temporal and/or inter-view prediction modes in units of predictionblocks, wherein the decoder is configured such that the firstsub-picture granularity subdivides the current picture in units ofprediction blocks.
 11. Decoder according to claim 9, wherein the decoderis configured to perform the reconstruction of the third componentsignal relating to a third component of the multi-component picture orvideo using spatial, temporal and/or inter-view prediction and byinverse-transforming a prediction residual of the spatial, temporaland/or inter-view prediction in units of transform blocks, wherein thedecoder is configured such that the first sub-picture granularitysubdivides the current picture in units of transform blocks.
 12. Decoderaccording to claim 9, wherein the decoder is configured to extract theweights from the ICP prediction parameter signalization in the datastream at a non-uniform quantization which is asymmetric with respect tozero.
 13. Decoder according to claim 9, wherein the decoder isconfigured to extract the weights from the ICP prediction parametersignalization in the data stream with zero belonging to a set ofpossible values of the weights, and wherein the decoder is configuredto, for each of blocks of a current picture of the multi-componentpicture or video, check whether the weight for the respective block iszero according to the ICP prediction parameter signalization, and ifnot, extract a ICP source indicator for the respective block from thedata stream, and if yes, suppress the extraction of the ICP sourceindicator for the respective block, wherein the decoder is configuredto, if the weight for the respective block is not zero, be responsive tothe ICP source indicator for the respective block so as to reconstructthe third component signal in the respective block using linearprediction from a spatially corresponding block of the reconstructedfirst component signal, weighted according to the respective non-zeroweight, or reconstruct the third component signal in the respectiveblock using linear prediction from a spatially corresponding block ofthe reconstructed second component signal, weighted according to therespective non-zero weight.
 14. Decoder according to claim 9, whereinthe decoder is configured to extract the weights from the ICP predictionparameter signalization in the data stream with zero belonging to a setof possible values of the weights, and wherein the decoder is configuredto, for each of blocks of a current picture of the multi-componentpicture or video, check whether the weight for the respective blockaccording to the ICP prediction parameter signalization fulfills apredetermined criterion, and if not, extract a ICP source indicator forthe respective block from the data stream, and if yes, suppress theextraction of the ICP source indicator for the respective block and setthe ICP source indicator for the respective block to a predeterminedstate, wherein the decoder is configured to be responsive to ICP sourceindicator for the respective block so as to reconstruct the thirdcomponent signal in the respective block using linear prediction from aspatially corresponding block of the reconstructed first componentsignal, weighted according to the weight for the respective block, orreconstruct the third component signal in the respective block usinglinear prediction from a spatially corresponding block of thereconstructed second component signal, weighted according to the weightfor the respective block.
 15. Decoder according to claim 9, wherein thedecoder is configured to extract the weights from the ICP predictionparameter signalization in the data stream by decoding the weights' signfirst and decoding the absolute value thereof using context-modelingdepending on the sign.
 16. Decoder according to claim 1, wherein thedecoder is configured to perform the reconstruction of the thirdcomponent signal relating to a third component of the multi-componentpicture or video using spatial, temporal and/or inter-view predictionwith applying the inter-component prediction onto a prediction residualof the spatial, temporal and/or inter-view prediction.
 17. Decoderaccording to claim 16, wherein the decoder is configured to performintra-component spatial, temporal and/or inter-view prediction withrespect to the first and second components of the multi-component audiosignals and is configured such that the reconstructed first componentsignal and the reconstructed second component signal are predictionresiduals of the intra-component spatial, temporal and/or inter-viewprediction performed with respect to the first and second components ofthe multi-component audio signals.
 18. Decoder according to claim 1,wherein the decoder is configured to perform the reconstruction of thethird component signal relating to a third component of themulti-component picture or video using intra-component spatial, temporaland/or inter-view prediction and by inverse-transforming a predictionresidual of the intra-component spatial, temporal and/or inter-viewprediction from spectral domain to spatial domain and apply theinter-component prediction onto the prediction residual in the spatialdomain or the spectral domain.
 19. Decoder according to claim 18,wherein the decoder is configured to perform the reconstruction of thefirst and second component signals using intra-component spatial,temporal and/or inter-view prediction.
 20. Decoder according to claim 1,wherein the decoder is configured to switch, at a first sub-picturegranularity, between reconstructing the third component signal in acurrent picture of the multi-component picture or video usinginter-component prediction from a spatially corresponding portion of thereconstructed first component signal and reconstructing the thirdcomponent signal in the current picture of the multi-component pictureor video using inter-component prediction from a spatially correspondingportion of the reconstructed second component signal and perform theinter-component prediction from the reconstructed first component signaland the reconstructed second component signal using a predeterminedprediction model with varying, responsive to ICP prediction parametersignalization in the data stream, a prediction parameter of theprediction model at a second sub-picture granularity, wherein thedecoder is configured to perform the switching at the first sub-picturegranularity responsive to an explicit ICP source signalization in thedata stream and to decode the explicit ICP source signalization from thedata stream using context modeling which is dependent on the predictionparameter of the prediction model.
 21. Decoder according to claim 19,wherein the decoder is configured to use linear prediction as theprediction model controlled via a gradient as the prediction parameter.22. Decoder according to claim 19, wherein the decoder is configured tocheck for a current sub-portion of a current picture of themulti-component picture or video whether the gradient for thatsub-portion is positive or negative, and to perform the context modelingdependent on the check.
 23. Decoder according to claim 19, wherein thedecoder is configured to check for a current sub-portion of a currentpicture of the multi-component picture or video whether the gradient forthat sub-portion is within a predetermined interval, and to perform thecontext modeling dependent on the check.
 24. Decoder according to claim1, wherein the decoder is configured to extract, for a predeterminedsub-portion of a current picture of the multi-component picture orvideo, first and second prediction parameters from the data stream,perform the inter-component prediction from the reconstructed firstcomponent signal using a predetermined prediction model and the firstprediction parameter, perform the inter-component prediction from thereconstructed second component signal using the predetermined predictionmodel and the second prediction parameter, and linearly combine theinter-component prediction from the reconstructed first component signaland inter-component prediction from the reconstructed second componentsignal.
 25. Decoder according to claim 1, wherein the decoder isresponsive to a swap signalization in the data stream so as to, at athird sub-picture granularity, swap the reconstructed third componentsignal and the reconstructed second component signal.
 26. Decoderaccording to claim 1, wherein the decoder is configured to perform theinter-component prediction from the reconstructed first component signaland the reconstructed second component signal using a predeterminedprediction model with varying, responsive to ICP prediction parametersignalization for the third component signal in the data stream, athird-component prediction parameter of the prediction model atsub-picture granularity, and perform the reconstruction of the secondcomponent signal relating to the second component of the multi-componentpicture or video using inter-component prediction from the reconstructedfirst component signal, and perform the inter-component prediction fromthe reconstructed first component signal using the predeterminedprediction model with varying, responsive to ICP prediction parametersignalization for the second component signal in the data stream, acomponent-signal prediction parameter of the prediction model atsub-picture granularity, and check where the second-component andthird-component prediction parameter differ by more than a predeterminedlimit, and for locations where not, extract a ICP source indicator forthe respective location from the data stream, and for locations whereyes, suppress the extraction of the ICP source indicator and set the ICPsource indicator for the respective location to a predetermined state,wherein the decoder is configured to be responsive to ICP sourceindicator so as to reconstruct the third component signal in therespective location using linear prediction from a spatiallycorresponding location of the reconstructed first component signal,weighted according to the respective third-component predictionparameter, or reconstruct the third component signal in the respectivelocation using linear prediction from a spatially corresponding locationof the reconstructed second component signal, weighted according to therespective third-component prediction parameter.
 27. Decoder accordingto claim 1, configured to, in reconstructing the third component signalrelating to the third component of the multi-component picture or video,extract a residual signal from the data stream for the third componentand correct the inter-component prediction thereby.
 28. Method fordecoding a multi-component picture or video spatially sampling a scenewith respect to different components, comprising reconstructing a firstcomponent signal relating to a first component of the multi-componentpicture or video from a data stream; reconstructing a second componentsignal relating to a second component of the multi-component picture orvideo from the data stream; reconstructing a third component signalrelating to a third component of the multi-component picture or videousing inter-component prediction from the reconstructed first componentsignal and the reconstructed second component signal.
 29. Encoderconfigured to encode a multi-component picture or video spatiallysampling a scene with respect to different components, by encoding afirst component signal relating to a first component of themulti-component picture or video into a data stream; encoding a secondcomponent signal relating to a second component of the multi-componentpicture or video into the data stream; encoding a third component signalrelating to a third component of the multi-component picture or videousing inter-component prediction from the encoded first component signaland the encoded second component signal.
 30. Method for encoding amulti-component picture or video spatially sampling a scene with respectto different components, comprising encoding a first component signalrelating to a first component of the multi-component picture or videointo a data stream; encoding a second component signal relating to asecond component of the multi-component picture or video into the datastream; encoding a third component signal relating to a third componentof the multi-component picture or video using inter-component predictionfrom the encoded first component signal and the encoded second componentsignal.
 31. A non-transitory digital storage medium having a computerprogram stored thereon to perform the method according to claim 28 whensaid computer program is run by a computer.
 32. A non-transitory digitalstorage medium having a computer program stored thereon to perform themethod according to claim 30 when said computer program is run by acomputer.